Abstract

Whilst several existing studies on foreign language learning have explored motivation in more traditional settings (Dörnyei, 2003), this paper presents one of the first studies on the motivation of participants in a MOOC.

The MOOC, Travailler en français (https://sites.google.com/site/mooctravaillerenfrancais/home), was a 5-week open online course for learners of French at level B1 of the CEFR, and aimed to develop language and employability skills for working in a francophone country. It took place in early 2014 and attracted more than 1000 participants.

Intrinsic motivation (Wigfield & Eccles, 2000), is directly linked to one’s enjoyment of accomplishing a task. We conducted a study based on the cognitive variables of the Self-Determination Theory (Deci & Ryan, 1985), and adapted the Intrinsic Motivation Inventory to the context of a MOOC in order to understand the expectancy beliefs and task values of participants engaging with the MOOC.

Participants answered a 40 Likert-type questions on enjoyment/ interest (i.e. I will enjoy doing this MOOC very much), perceived competence (i.e. I think I will be able to perform successfully in the MOOC), effort (i.e. I will put a lot of effort in this MOOC), value/usefulness (i.e. I think that doing this MOOC will be useful for developing my skills), felt pressure and tension (i.e. I think I might feel pressured while doing the MOOC) and relatedness (i.e. I think I will feel like I can really trust the other participants).

Results highlight significant factors that could directly influence intrinsic motivation for learning in a MOOC environment. The chapter makes recommendations for LMOOC designers based on the emerging profile of MOOC participants, on their motivation and self-determination, as well as on the pressures they might feel, including time pressures. Finally, the extent to which participants relate to each other, and are able to engage in social learning and interaction, is a real challenge for LMOOC designers.

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.